In this talk, I will be walking through some analysis of Labor Trafficking Data. I'll be analyzing the types of goods that slaves are forced to make, what countries they come from, and how this affects GDP as well as other economic measures in those countries. I will cover Exploratory Data Analysis, Data Cleaning, Feature Engineering, Regression Analysis, and modeling and model work flows. I'll explore how to understand and interpret linear as well as non-linear models and use these models to explain the underlying data. All analysis will leverage standard tools in Python, including scikit learn, pandas, matplotlib, and possibly other tools.

Biographical Notes

Eric Schles works for Elucd as a Data Scientist, Adjunct Professor at NYU, and researcher at NYU. He specializes in using big data to combat human trafficking. He has worked for the Manhattan DA's Human Trafficking Response Unit, serving as Senior Analyst and for the White House under the Obama Administration in the past. He is deeply passionate about solving slavery and using data science and automation to do it. His research at NYU focuses on combating human trafficking as well